Session A48: Focus Session: Physics of Protein: Allosteric Control

An explicitly solvated full atomistic model of the cardiac thin filament and application on the calcium binding affinity effects from familial hypertrophic cardiomyopathy linked mutations

The previous version of our cardiac thin filament (CTF) model consisted of the troponin complex (cTn), two coiled-coil dimers of tropomyosin (Tm), and 29 actin units. We now present the newest revision of the model to include explicit solvation. The model was developed to continue our study of genetic mutations in the CTF proteins which are linked to familial hypertrophic cardiomyopathies. Binding of calcium to the cTnC subunit causes subtle conformational changes to propagate through the cTnC to the cTnI subunit which then detaches from actin. Conformational changes propagate through to the cTnT subunit, which allows Tm to move into the open position along actin, leading to muscle contraction. Calcium disassociation allows for the reverse to occur, which results in muscle relaxation. The inclusion of explicit TIP3 water solvation allows for the model to get better individual local solvent to protein interactions; which are important when observing the N-lobe calcium binding pocket of the cTnC. We are able to compare in silica and in vitro experimental results to better understand the physiological effects from mutants, such as the R92L/W and F110V/I of the cTnT, on the calcium binding affinity compared to the wild type.   

Proteins and Complexity

A protein's tertiary structure determines its function in living organisms. The different functions proteins serve necessitate variety in native structures. How is variation in tertiary structure created from a common set of amino acids and molecular forces? In other words, what generates complexity in structures across all types of native proteins? To explore this question, a simple HP model of protein folding was explored for evidence of self-organized criticality, a potential generator of complexity.   

Interaction and dynamics of homologous pairing protein 2 (HOP2) and DNA studied by MD simulation

The homologous pairing protein 2 (Hop2) plays an important role in meiosis and DNA repair. Together with protein Mnd1, Hop2 enhances the strand invasion activity of recombinase Dmc1 by over 30 times, facilitating proper synapsis of homologous chromosomes. We recently determined the NMR structure of the N-terminal domain of Hop2 and proposed a model of Protein-DNA complex based on NMR chemical shift perturbations and mutagenesis studies (Moktan, J Biol Chem 2014 10.1074/jbc.M114.548180). However structure and dynamics of the complex have not been studied at the atomic level yet. Here, we used classical MD simulations to study the interactions between the N-terminal HOP2 and DNA. The simulated results indicate that helix3 (H3) interacts with DNA in major groove and wing1 (W1) interacts mostly in minor groove mainly via direct hydrogen bonds. Also it is found that binding leads to reduced fluctuations in both protein and DNA. Several water bridge interactions have been identified. The residue-wise contributions to the interaction energy were evaluated. Also the functional motion of the protein is analyzed using principal component analysis. The results confirmed the importance of H3 and W1 for the stability of the complex, which is consistent with our previous experimental studies.   

Principles of allosteric mechanisms in cell signaling

Linking cell signaling events to the fundamental physicochemical basis of the conformational behavior of single molecules and ultimately to cellular function are key challenges facing the life sciences. Specific protein function is determined by the extent to which the protein populates a distinct active state. Allostery, an inherent physical property of proteins, is a key factor governing the relative populations among accessible conformational states. Allostery can be defined as the change in the distribution of the conformational ensemble through some perturbation. Nature has co-evolved ligand-host protein interactions, optimizing them to tune the populations of the active (or inactive) states for function, either by stabilizing the active conformation and/or destabilizing the inactive conformations, or vice versa. More and more data attest to the significance of allostery in cell life under physiological conditions and in disease. We aim to delineate key challenging questions, such as can we predict a priori- and quantify- changes incurred by allosteric mutations or specific binding events to increase/decrease the population of the active or inactive state to up- or down- regulate the protein? I will provide an overview of the fundamental underpinnings of allostery.   

Interaction of albumin with perylene-diimides with aromatic substituents

Polyaromatic hydrocarbons (PAH) binding to proteins remains one of the fundamental aspects of research in biophysics. Ligand binding can regulate the function of proteins. Binding to small ligands remains a very important aspect in the study of the function of many proteins. Perylene diimide or PDI derivatives have attracted initial interest as industrial dyes and pigments. Recently, much attention has been focused on their strong$\pi -\pi $ stacks resulting from the large PDI aromatic core. These PDI stacks have distinct optical properties, and provide informative models that mimic the light-harvesting system and initial charge separation and charge transfer in the photosynthetic system. The absorption property of PDI derivatives may be largely tuned from visible to near-infrared region by chemical modifications at the bay-positions. We are currently studying a new class of PDI derivatives with substituents made of the side chains of aromatic amino acids (Tyrosine, Tryptophan and Phenylalanine). We have looked at the fluorescence absorption and emission of these PDIs in water and other organic solvents. PDIs show evidence of dimerization and possible aggregation. We also present binding studies of these PDIs with Human Serum Albumin (HSA). The binding was studied using fluorescence emission quenching of the HSA Tryptophan residue. Stern-Volmer equation is used to derive the quenching constants. PDI binding to HSA also has an effect on the fluorescence emission of the PDIs themselves by red shifting the spectra.   

Probing a Conformational Change of a Photoswitchable Allosteric Protein with Ultrafast IR Spectroscopy

By covalently linking an azobenzene photoswitch across the binding groove of an allosteric protein domain, a conformational transition can be initiated by a laser pulse.\footnote{Buchli, B. \textit{et al.} Kinetic response of a photoperturbed allosteric protein. \textit{Proceedings of the National Academy of Sciences of the United States of America} \textbf{110}, 11725-30 (2013).} This transition mimics the conformational change of the unmodified domain upon ligand binding. We have studied this light induced conformational change by ultrafast IR spectroscopy. So far, we have probed two IR absorption bands: First, the amide~I band which arises from the carbonyl stretch vibration of all amide groups in the protein and is sensitive to overall structural changes, and second, a vibration localized on the photoswitch, which is sensitive to its local environment, namely the opening of the binding groove. We have found that the binding groove opens on a timescale of 100~ns in a non-exponential manner. Even after the binding groove has equilibrated, the protein conformation still continues to change elsewhere. Currently, we are incorporating site-specific IR labels, to learn more about the response of the protein to the perturbation of the binding groove.   

Global Low Frequency Protein Motions in Long-Range Allosteric Signaling

We present a foundational theory for how allostery can occur as a function of low frequency dynamics without a change in protein structure. Elastic inhomogeneities allow entropic ``signalling at a distance.'' Remarkably, many globular proteins display just this class of elastic structure, in particular those that support allosteric binding of substrates (long-range co-operative effects between the binding sites of small molecules). Through multi-scale modelling of global normal modes we demonstrate negative co-operativity between the two cAMP ligands without change to the mean structure. Crucially, the value of the co-operativity is itself controlled by the interactions around a set of third allosteric ``control sites.'' The theory makes key experimental predictions, validated by analysis of variant proteins by a combination of structural biology and isothermal calorimetry. A quantitative description of allostery as a free energy landscape revealed a protein ``design space'' that identified the key inter- and intramolecular regulatory parameters that frame CRP/FNR family allostery. Furthermore, by analyzing naturally occurring CAP variants from diverse species, we demonstrate an evolutionary selection pressure to conserve residues crucial for allosteric control. The methodology establishes the means to engineer allosteric mechanisms that are driven by low frequency dynamics.   

Functionally important residues from mode coupling during short-time protein dynamics

Relevance of mode coupling to energy/information transfer during protein function, particularly in the context of allosteric interactions is widely accepted. However, existing evidence in favor of this hypothesis comes essentially from model systems. We here report a novel formal analysis of the near-native dynamics for proteins, which allows us to explore the impact of the interaction between possibly non-Gaussian vibrational modes on fluctutational dynamics. We show that, an information-theoretic measure based on mode coupling {\it alone} yields a ranking of residues with a statistically significant bias favoring the functionally critical locations identified by experiments on Myosin II and AncGR1,2. \\ Reference: O. Varol et al., Proteins: Structure, Function and Bioinformatics, 82(9), 1777 (2014).   

Optical observation of correlated motions in dihydrofolate reductase

Enzyme function relies on its structural flexibility to make conformational changes for substrate binding and product release. An example of a metabolic enzyme where such structural changes are vital is dihydrofolate reductase (DHFR). DHFR is essential in both prokaryotes and eukaryotes for the nucleotide biosynthesis by catalyzing the reduction of dihydrofolate to tetrahydrofolate. NMR dynamical measurements found large amplitude fast dynamics that could indicate rigid-body, twisting-hinge motion for ecDHFR that may mediate flux [1]. The role of such long-range correlated motions in function was suggested by the observed sharp decrease in enzyme activity for the single point mutation G121V, which is remote from active sites[2]. This decrease in activity may be caused by the mutation interfering with the long-range intramolecular vibrations necessary for rapid access to functional configurations. We use our new technique of crystal anisotropy terahertz microscopy (CATM)[3], to observe correlated motions in ecDHFR crystals with the bonding of NADPH and methotrexate. We compare the measured intramolecular vibrational spectrum with calculations using normal mode analysis. 1. Cameron C.E. and Benkovic S.J., \textit{Biochemistry}, 1997. 36(50): p. 15792-15800. 2. Bhabha G., et al., \textit{Nat Struct Mol Biol}, 2013. 20(11): p. 1243-9. 3. Acbas, G., Niessen K.A., Snell E. H., and Markelz A.G., \textit{Nat Commun}, 2014. 5, 3076.   

Non-linear dynamics in recurrently connected neural circuits implement Bayesian inference by sampling

Experimental evidence at the behavioural-level shows that the brains are able to make Bayes-optimal inference and decisions (Kording and Wolpert 2004, Nature; Ernst and Banks, 2002, Nature), yet at the circuit level little is known about how neural circuits may implement Bayesian learning and inference (but see (Ma et al. 2006, Nat Neurosci)). Molecular sources of noise are clearly established to be powerful enough to pose limits to neural function and structure in the brain (Faisal et al. 2008, Nat Rev Neurosci; Faisal et al. 2005, Curr Biol). We propose a spking neuron model where we exploit molecular noise as a useful resource to implement close-to-optimal inference by sampling. Specifically, we derive a synaptic plasticity rule which, coupled with integrate-and-fire neural dynamics and recurrent inhibitory connections, enables a neural population to learn the statistical properties of the received sensory input (prior). Moreover, the proposed model allows to combine prior knowledge with additional sources of information (likelihood) from another neural population, and to implement in spiking neurons a Markov Chain Monte Carlo algorithm which generates samples from the inferred posterior distribution.